title: Inferring molecular function: contributions from functional linkages.
abstract: In the current era of high-throughput sequencing and structure determination, functional annotation has become a bottleneck in biomedical science. Here, we show that automated inference of molecular function using functional linkages among genes increases the accuracy of functional assignments by > or =8% and enriches functional descriptions in > or =34% of top assignments. Furthermore, biochemical literature supports >80% of automated inferences for previously unannotated proteins. These results emphasize the benefit of incorporating functional linkages in protein annotation.
authors.affiliation: Howard Hughes Medical Institute (HHMI), 675C. E. Young Drive South, Los Angeles, CA 90095, USA.
authors.forename: Arturo
authors.initials: A
authors.lastname: Medrano-Soto
authors.forename: Debnath
authors.initials: D
authors.lastname: Pal
authors.forename: David
authors.initials: D
authors.lastname: Eisenberg
mesh_terms: D008040:Genetic Linkage; D011506:Proteins / Q000378:metabolism*
chemical_list: D011506:Proteins